Evidence map›Paper›PMID 31656670›Full record

ArticleJournal of thoracic disease2019

Discovery of potential plasma protein biomarkers for acute myocardial infarction via proteomics.

Shasha Xu, Jianjun Jiang, Yang Zhang, Tingting Chen, Min Zhu, Chongfeng Fang, Yafei Mi

Open access · diamondAbstract read
In one paragraph

Article in Journal of thoracic disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 39 citations in OpenAlex.

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  6. Deciphering Acute Coronary Syndromes Pathobiology Through Proteomics.Journal of cardiovascular development and disease · 2025
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  15. Various Expressions ofBiomolecules · 2023
    Article
  16. Article
  17. IGFBP-6: At the Crossroads of Immunity, Tissue Repair and Fibrosis.International journal of molecular sciences · 2022
    Review
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Shasha XuDepartment of Cardiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Jianjun JiangDepartment of Cardiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Yang ZhangDepartment of Cardiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Tingting ChenDepartment of Cardiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Min ZhuEnze Medical Research Center, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Chongfeng FangDepartment of Cardiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Yafei MiDepartment of Cardiology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou 317000, China.
Wenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute myocardial infarction (AMI) is an acute disease with high mortality and seriously threatens human health. The identification of new effective biological markers for AMI is a prerequisite for treatment. Most proteomic studies have focused on atherosclerotic plaques, vascular cells, monocytes and platelets in the blood; however, the concentration of these factors in plasma is low, making it difficult to measure the complexity of plasma components. Moreover, some studies have examined the plasma protein of patients with acute coronary syndrome with histochemistry; however, the results are not consistent. Therefore, it is necessary to further investigate the differential proteins in the plasma of patients with AMI via proteomics to identify new biomarkers of AMI.

methodsIn this study, immunodepletion of high-abundance plasma proteins followed by an isobaric tagging for relative and absolute quantitation (iTRAQ)-based quantitative proteomic approach was used to analyze plasma samples from 5 control individuals and 10 AMI patients.

resultsFour hundred sixty-eight proteins were identified from two samples, and 33 proteins were differentially expressed in AMI patients compared to the controls. Among the 33 proteins, 12 proteins showed a ≥1.5-fold change between AMI and control samples. These proteins included fatty acid binding protein 3 (FABP3, ratio =6.36), creatine kinase-MB (CK-MB ratio =4.89), adenylate kinase1 (AK1 ratio =4.16), pro-platelet basic protein (PPBP ratio =3.29), creatine kinase (CK ratio =2.88), platelet factor 4 (PF4 ratio =2.62), peptidyl prolyl isomerase Cyclophilin A (PPIA ratio =2.05), Cofilin-1 (CFL1 ratio =1.81), coronin1A (CORO1A ratio =1.71), protein kinase M (PKM ratio =1.63), ribonuclease inhibitor (RNH1, ratio =1.67), and triose phosphate isomerase (TPI1 ratio =1.56). By contrast, there was a decrease of 19 proteins, such as adiponectin (ADIPOQ ratio =0.70), insulin-like growth factor binding protein6 (IGFBP6 ratio =0.70), Dickkopf-related protein 3 (DKK3 ratio =0.70) and complement 4B (C4B ratio =0.68). The most over-represented term was regulation of cell proliferation in the cellular component category of Gene Ontology (GO). The top 3 biological process terms were regulation of cell proliferation, response to wounding and wound healing. These proteins included immune proteins, blood coagulation proteins, lipid metabolism proteins, cytoskeleton proteins, energy metabolism proteins, gene regulation proteins, myocutaneous proteins, and myocardial remodeling proteins and were highly connected with each other, which indicates that the functional network of these processes contribute to the pathophysiology of AMI.

conclusionsIn conclusion, the present quantitative proteomic study identified novel AMI biomarker candidates and might provide fundamental information for the development of an AMI biomarker.

Indexed as

acute myocardial infarction (AMI)Plasma protein biomarkersproteomics

Identifiers

PMID31656670
PMCPMC6790472
OpenAlexW2972817501

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.